Abiotic Stress Tolerance in Field Crops: Integration of Omics Approaches

  • Zahide Neslihan Ozturk GokceEmail author
  • Seyda Akbas
  • Sefa Ayten
  • M. Hussain Azimi
  • Reyhan Das
  • Saime Buse Guven
  • Ebrar Karabulut
  • Seher Omezli
  • Zehra Uzer
  • Bayram Ali Yerlikaya
  • Allah Bakhsh


The development, growth, and productivity of field crops are negatively influenced by abiotic stresses resulting in significant losses in crop yield. Therefore, understanding tolerance of agronomic crops to abiotic stress factors like drought, salinity, heat, and chilling is of paramount importance for plant scientists for effective management. However, due to the complexity of abiotic stress response and tolerance, initial efforts through gene-based approaches were not enough to understand whole level mechanisms. Recently, tremendous developments made in the field of omics (genomics, transcriptomics, proteomics, metabolomics, and phenomics) have opened new avenues to understand and investigate the complex mechanisms of abiotic stress tolerance in plants, although integration of data collected from omics studies with such traits is still a challenging one. This chapter will emphasize the significance of omics field in understanding crop responses to different abiotic stresses, focusing on the recent developments made in field of omics with future prospects to overcome the major drawbacks of omic approaches.


Abiotic stress Omics Omic technologies Genomics Transcriptomics Proteomics Metabolomics Ionomics Lipidomics Phenomics Complex traits Combined stress Wild type Data integration Systems biology 



2-dimensional polyacrylamide gel electrophoresis


abscisic acid


capillary electrophoresis mass spectroscopy


enhanced green fluorescent protein


Fourier transform ion cyclotron resonance mass spectroscopy

G x E

genotype–environment interaction


genotyping by sequencing


gas-chromatography mass spectroscopy


genome-wide association study


inductively coupled plasma mass spectrometer


inductively coupled plasma-optical emission spectrometry


laser ablation inductively coupled plasma mass spectroscopy


liquid-chromatography mass spectroscopy


matrix-assisted laser desorption/ionization time-of-flight


marker-assisted selection


metabolite quantitative trait locus


mass spectroscopy


molecular weight


neutron activation analysis


next-generation sequencing


nuclear magnetic resonance


isoelectric point


quantitative trait loci


reactive oxygen species


single-nucleotide polymorphism


X-ray absorption spectroscopy


X-ray fluorescence



All authors have equally contributed to the writing of this chapter. The corresponding author, Zahide Neslihan Ozturk Gokce, wants to acknowledge their tremendous effort in literature search of this wide topic. We would like to apologize to the scientists whose work and publication have not been emphasized in this chapter due to page limitations.


  1. Abreu IA, Farinha AP, Negrao S, Gonçalves N, Fonseca C, Rodrigues M, Batista R, Saibo NJM, Oliveria MM (2013) Coping with abiotic stress: proteome changes for crop improvement. J Proteome 93:145–168CrossRefGoogle Scholar
  2. Agarwal GK, Pedreschi R, Barkla BJ, Bindshedler LV, Cramer R, Sarkar A, Renault J, Job D, Rakwal R (2012) Translational plant proteomics: a perspective. J Proteome 75:4588–4601CrossRefGoogle Scholar
  3. Agarwal P, Parida SK, Mahto A, Das S, Mathew IE, Malik N, Tyagi AK (2014) Expanding frontiers in plant transcriptomics in aid of functional genomics and molecular breeding. Biotechnol J 9:1480–1492PubMedCrossRefGoogle Scholar
  4. Agrawal L, Gupta S, Mishra SK, Pandey G, Kumar S, Chauhan PS, Chakrabarty D, Nautiyal CS (2016) Elucidation of complex nature of PEG induced drought-stress response in rice root using comparative proteomics approach. Front Plant Sci 7:1466PubMedPubMedCentralCrossRefGoogle Scholar
  5. Ahsan N, Donnart T, Nouri MZ, Komatsu S (2010) Tissue-specific defense and thermo-adaptive mechanisms of soybean seedlings under heat stress revealed by proteomic approach. J Proteome Res 9:4189–4204PubMedCrossRefGoogle Scholar
  6. Alagoz SM, Toorchi M (2018) An investigation of some key morpho-physiological attributes and leaf proteome profile in canola (Brassica napus L.) under salinity stress. Pak J Bot 50:847–852Google Scholar
  7. Alexandersson E, Jacobson D, Vivier MA, Weckwerth W, Andreasson E (2014) Field-omics – understanding large-scale molecular data from field crops. Front Plant Sci 5:286PubMedPubMedCentralCrossRefGoogle Scholar
  8. Alseekh S, Fernie AR (2018) Metabolomics 20 years on: what have we learned and what hurdles remain? Plant J 94:933–942PubMedCrossRefGoogle Scholar
  9. Alvarez S, Roy Choudhury S, Pandey S (2014) Comparative quantitative proteomics analysis of the ABA response of roots of drought-sensitive and drought-tolerant wheat varieties identifies proteomic signatures of drought adaptability. J Proteome Res 13:1688–1701PubMedCrossRefGoogle Scholar
  10. Ashraf MA, Akbar A, Askari SH, Iqbal M, Rasheed R, Hussain I (2018) Recent advances in abiotic stress tolerance of plants through chemical priming: an overview. In: Rakshit A, Singh H (eds) Advances in seed priming. Springer, Singapore, pp 51–59CrossRefGoogle Scholar
  11. Barkla BJ, Vera-Estrella R, Pantoja O (2013) Progress and challenges for abiotic stress proteomics of crop plants. Proteomics 13:1801–1815PubMedCrossRefGoogle Scholar
  12. Barrero-Sicilia C, Silvestre S, Haslam RP, Michaelson LV (2017) Lipid remodelling: unravelling the response to cold stress in Arabidopsis and its extremophile relative Eutrema salsugineum. Plant Sci 263:194–200PubMedPubMedCentralCrossRefGoogle Scholar
  13. Batayeva D, Labaco B, Ye C, Li X, Usenbekov B, Rysbekova A, Dyuskalieva G, Vergara G, Reinke R, Leung H (2018) Genome-wide association study of seedling stage salinity tolerance in temperate japonica rice germplasm. BMC Genet 19(2):1–11Google Scholar
  14. Baxter I (2015) Should we treat the ionome as a combination of individual elements, or should we be deriving novel combined traits? J Exp Bot 66:2127–2731PubMedPubMedCentralCrossRefGoogle Scholar
  15. Baytar AA, Peynircioğlu C, Sezener V, Basal H, Frary A, Frary A, Doğanlar S (2018) Genome-wide association mapping of yield components and drought tolerance-related traits in cotton. Mol Breed 38:74CrossRefGoogle Scholar
  16. Cai C, Wu S, Niu E, Cheng C, Guo W (2017) Identification of genes related to salt stress tolerance using intron length polymorphic markers, association mapping and virus induced gene silencing in cotton. Sci Rep 7:528PubMedPubMedCentralCrossRefGoogle Scholar
  17. Capriotti AL, Borrelli GM, Colapicchioni V, Papa R, Piovesana S, Samperi R, Stampachiacchiere S, Lagana A (2014) Proteomic study of a tolerant genotype of durum wheat under salt-stress conditions. Anal Bioanal Chem 406:1423–1435PubMedCrossRefGoogle Scholar
  18. Charlton AJ, Donarski JA, Harrison M, Jones SA, Godward J, Oehlschlager S, Arques JL, Ambrose M, Chinoy C, Mullineaux PM, Domoney C (2008) Responses of the pea (Pisum sativum L.) leaf metabolome to drought stress assessed by nuclear magnetic resonance spectroscopy. Metabolomics 4:312–327CrossRefGoogle Scholar
  19. Chebrolu KK, Fritschi FB, Ye S, Krishnan HB, Smith JR, Gillman JD (2016) Impact of heat stress during seed development on soybean seed metabolome. Metabolomics 12:1–14CrossRefGoogle Scholar
  20. Chen S, Gollop N, Heuer B (2009) Proteomic analysis of salt-stressed tomato (Solanum lycopersicum) seedlings: effect of genotype and exogenous application of glycine betaine. J Exp Bot 60:2005–2019PubMedPubMedCentralCrossRefGoogle Scholar
  21. Chen K, Renaut J, Sergeant K, Wei H, Arora R (2013) Proteomic changes associated with freeze-thaw injury and post-thaw recovery in onion (Allium cepa L.) scales. Plant Cell Environ 36:892–905PubMedCrossRefGoogle Scholar
  22. Chintakovid N, Maipoka M, Phaonakrop N, Mickelbart MV, Roytrakul S, Chadchawan S (2017) Proteomic analysis of drought-responsive proteins in rice reveals photosynthesis-related adaptations to drought stress. Acta Physiol Plant 39:240CrossRefGoogle Scholar
  23. Damaris RN, Li M, Liu Y, Chen X, Murage H, Yang P (2016) A proteomic analysis of salt stress response in seedlings of two African rice cultivars. Biochim Biophys Acta 1864:1570–1578PubMedCrossRefGoogle Scholar
  24. Debnath M, Pandey M, Bisen PS (2011) An omics approach to understand the plant abiotic stress. OMICS 15:739–762PubMedCrossRefGoogle Scholar
  25. Deshmukh V, Mankar SP, Muthukumar C, Divahar P, Bharathi A, Thomas HB, Rajurkar A, Sellamuthu R, Poornima R, Senthivel S, Babu CR (2018) Genome-wide consistent molecular markers associated with phenology, plant production and root traits in diverse rice (Oryza sativa L.) accessions under drought in rainfed target populations of the environment. Curr Sci 114:329–340CrossRefGoogle Scholar
  26. Dias DA, Hill CB, Jayasinghe NS, Atieno J, Sutton T, Roessner U (2015) Quantitative profiling of polar primary metabolites of two chickpea cultivars with contrasting responses to salinity. J Chromatogr 1000:1–13Google Scholar
  27. Ding H, Han Q, Ma D, Hou J, Huang X, Wang C, Xie Y, Kang G, Guo T (2017) Characterizing physiological and proteomic analysis of the action of H2S to mitigate drought stress in young seedling of wheat. Plant Mol Biol Report 36:45–57CrossRefGoogle Scholar
  28. Du L, Cai C, Wu S, Zhang F, Hou S, Guo W (2016) Evaluation and exploration of favorable QTL alleles for salt stress related traits in cotton cultivars (G. hirsutum L.). PLoS One 11:e0151076PubMedPubMedCentralCrossRefGoogle Scholar
  29. ElBasyoni I, Saadalla M, Baenziger S, Bockelman H, Morsy S (2017) Cell membrane stability and association mapping for drought and heat tolerance in a worldwide wheat collection. Sustain For 9:1606CrossRefGoogle Scholar
  30. Elwafa SFA (2016) Association mapping for yield and yield-contributing traits in barley under drought conditions with genome-based SSR markers. CR Biol 339:153–162CrossRefGoogle Scholar
  31. Ereful NC, Liu LY, Tsai E, Kao SM, Dixit S, Mauleon R, Malabanan K, Thomson M, Laurena A, Lee D, Mackay I, Greenland A, Powell W, Leung H (2016) Analysis of allelic imbalance in rice hybrids under water stress and association of asymmetrically expressed genes with drought-response QTLs. Rice 9:50PubMedPubMedCentralCrossRefGoogle Scholar
  32. Evers D, Legay S, Lamoureux D, Hausman JF, Hoffmann L, Renaut J (2012) Towards a synthetic view of potato cold and salt stress response by transcriptomic and proteomic analyses. Plant Mol Biol 78:503–514PubMedCrossRefGoogle Scholar
  33. Faghani E, Gharechahi J, Komatsu S, Mirzaei M, Khavarinejad RA, Najafi F, Farsad LK, Salekdeh GH (2014) Comparative physiology and proteomic analysis of two wheat genotypes contrasting in drought tolerance. J Proteome 114:1–15CrossRefGoogle Scholar
  34. Fahlgren N, Gehan MA, Baxter I (2015) Lights, camera, action: high-throughput plant phenotyping is ready for a close-up. Curr Opin Plant Biol 24:93–99PubMedCrossRefGoogle Scholar
  35. Farooq M, Hussain M, Wakeel A, Siddique KHM (2015) Salt stress in maize: effects, resistance mechanisms, and management. A review. Agron Sustain Dev 35:461–481CrossRefGoogle Scholar
  36. Feng K, Nie X, Cui L, Deng P, Wang M, Song W (2017) Genome-wide identification and characterization of salinity stress-responsive miRNAs in wild emmer wheat (Triticum turgidum ssp. dicoccoides). Gene 8:156CrossRefGoogle Scholar
  37. Fercha A, Capriotti AL, Caruso G, Cavaliere C, Samperi R, Stampachiacchiere S, Lagana A (2014) Comparative analysis of metabolic proteome variation in ascorbate-primed and unprimed wheat seeds during germination under salt stress. J Proteome 108:238–257CrossRefGoogle Scholar
  38. Fercha A, Capriotti AL, Caruso G, Cavaliere C, Stampachiacchiere S, Chiozzi RZ, Lagan A (2016) Shotgun proteomic analysis of soybean embryonic axes during germination under salt stress. Proteomics 16:1537–1546PubMedCrossRefGoogle Scholar
  39. Fields S, Song O (1989) A novel genetic system to detect protein-protein interactions. Nature 340:245–246PubMedCrossRefGoogle Scholar
  40. Ford KL, Cassin A, Bacic A (2011) Quantitative proteomic analysis of wheat cultivars with differing drought stress tolerance. Front Plant Sci 2:44PubMedPubMedCentralCrossRefGoogle Scholar
  41. Frouin J, Languillaume A, Mas J, Mieulet D, Boisnard A, Labeyrie A, Bettembourg M, Bureau C, Lorenzini E, Portefaix M, Turquay P, Vernet A, Perin C, Ahmadi N, Courtois B (2018) Tolerance to mild salinity stress in japonica rice: a genome-wide association mapping study highlights calcium signaling and metabolism genes. PLoS One 13:e0190964PubMedPubMedCentralCrossRefGoogle Scholar
  42. Fuhrer T, Zamboni N (2015) High-throughput discovery metabolomics. Curr Opin Biotechnol 31:73–78PubMedCrossRefGoogle Scholar
  43. Fukuda M, Islam N, Woo SH, Yamagishi A, Takaoka M, Hirano H (2003) Assessing matrix assisted laser desorption/ionization-time of flight-mass spectrometry as a means of rapid embryo protein identification in rice. Electrophoresis 24:1319–1329PubMedCrossRefGoogle Scholar
  44. Fumagalli E, Baldoni E, Abbruscato P, Piffanelli P, Genga A, Lamanna R, Consonni R (2009) NMR techniques coupled with multivariate statistical analysis: tools to analyse Oryza sativa metabolic content under stress conditions. J Agron Crop Sci 195:77–88CrossRefGoogle Scholar
  45. Furbank RT, Tester M (2011) Phenomics – technologies to relieve the phenotyping bottleneck. Trends Plant Sci 16:635–644PubMedCrossRefGoogle Scholar
  46. Gao R, Duan K, Guo G, Du Z, Chen Z, Li L, He T, Lu R, Huang J (2013) Comparative transcriptional profiling of two contrasting barley genotypes under salinity stress during the seedling stage. Int J Genomics 139:822–835Google Scholar
  47. Gavaghan CL, Li JV, Hadfield ST, Hole S, Nicholson JK, Wilson ID (2011) Application of NMR-based metabolomics to the investigation of salt stress in maize (Zea mays). Phytochem Anal 22:214–224PubMedCrossRefGoogle Scholar
  48. Ghatak A, Chaturvedi P, Nagler M, Roustan V, Lyon D, Bachmann G, Postl W, Schröfl A, Desai N, Varshney RK, Weckwerth W (2016) Comprehensive tissue-specific proteome analysis of drought stress responses in Pennisetum glaucum (L.) R. Br. (Pearl millet). J Proteome 43:122–135CrossRefGoogle Scholar
  49. Ghosh N, Adak MK, Ghosh PD, Gupta S, Sengupta DN, Mandal C (2011) Differential responses of two rice varieties to salt stress. Plant Biotech Rep 5:89–103CrossRefGoogle Scholar
  50. Gong FP, Yang L, Tai F, Hu XL, Wang W (2014) “Omics” of maize stress response for sustainable food production: opportunities and challenges. OMICS 18:714–732PubMedPubMedCentralCrossRefGoogle Scholar
  51. Gross RW (2017) The evolution of lipidomics through space and time. BBA - Mol Cell Biol L 1862:731–739CrossRefGoogle Scholar
  52. Guo G, Ge P, Ma C, Li X, Lv D, Wang S, Ma W, Yan Y (2012) Comparative proteomic analysis of salt response proteins in seedling roots of two wheat varieties. J Proteome 75:1867–1885CrossRefGoogle Scholar
  53. Guo R, Shi LX, Yan C, Zhong X, Gu FX, Liu Q, Xia X, Li H (2017) Ionomic and metabolic responses to neutral salt or alkaline salt stresses in maize (Zea mays L.) seedlings. BMC Plant Biol 17:41PubMedPubMedCentralCrossRefGoogle Scholar
  54. Guo Z, Yang W, Chang Y, Ma X, Tu H, Xiong F, Jiang N, Feng H, Huang C, Yang P, Zhao H, Chen G, Liu H, Luo L, Hu H, Liu Q, Xiong L (2018) Genome-wide association studies of image traits reveal genetic architecture of drought resistance in rice. Mol Plant 11:789–805PubMedCrossRefGoogle Scholar
  55. Gupta B, Sengupta A, Saha J, Gupta K (2013) Plant abiotic stress: ‘Omics’ approach. Plant Biochem Physiol 1:1000e108Google Scholar
  56. Hamilton JP, Buell CR (2012) Advances in plant genome sequencing. Plant J 70:177–190PubMedCrossRefGoogle Scholar
  57. Hasanuzzaman M, Hossain MA, Fujita M (2011) Selenium-induced up-regulation of the antioxidant defense and methylglyoxal detoxification system reduces salinity-induced damage in rapeseed seedlings. Biol Trace Elem Res 143:1704–1721PubMedCrossRefGoogle Scholar
  58. Hashimoto M, Komatsu S (2007) Proteomic analysis of rice seedlings during cold stress. Proteomics 7:1293–1302PubMedCrossRefGoogle Scholar
  59. Hashimoto M, Toorchi M, Matsushita K, Iwasaki Y, Komatsu S (2009) Proteome analysis of rice root plasma membrane and detection of cold stress responsive proteins. Protein Pept Lett 16:685–697PubMedCrossRefGoogle Scholar
  60. Hayward SAL (2014) Application of functional ‘omics’ in environmental stress physiology: insights, limitations, and future challenges. Curr Opin Insect Sci 4:35–41PubMedCrossRefGoogle Scholar
  61. Hazzouri KM, Khraiwesh B, Amiri KMA, Pauli D, Blake T, Shahid M, Mullath SK, Nelson D, Mansour AL, Salehi-Ashtiani K, Purugganan M, Masmoudi K (2018) Mapping of HKT1:5 gene in barley using GWAS approach and its implication in salt tolerance mechanism. Front Plant Sci 9:156PubMedPubMedCentralCrossRefGoogle Scholar
  62. He J, Zhao X, Laroche A, Lu ZX, Liu H, Li Z (2014) Genotyping-by-sequencing (GBS), an ultimate marker-assisted selection (MAS) tool to accelerate plant breeding. Front Plant Sci 5:484PubMedPubMedCentralCrossRefGoogle Scholar
  63. Hong J, Yang L, Zhang D, Shi J (2016) Plant metabolomics: an indispensable system biology tool for plant science. Int J Mol Sci 17:767PubMedCentralCrossRefPubMedGoogle Scholar
  64. Hu G, Li Z, Lu Y, Li C, Gong S, Yan S, Li G, Wang M, Ren H, Guan H, Zhang Z, Qin D, Chai M, Yu J, Li Y, Yang D, Wang T, Zhang Z (2017) Genome-wide association study identified multiple genetic loci on chilling resistance during germination in maize. Sci Rep 7:10840PubMedPubMedCentralCrossRefGoogle Scholar
  65. Huang XY, Salt DE (2016) Plant ionomics: from elemental profiling to environmental adaptation. Mol Plant 9:787–797PubMedCrossRefGoogle Scholar
  66. Humplik JF, Lazar D, Husicova A, Spichal L (2015) Automated phenotyping of plant shoots using imaging methods for analysis of plant stress responses – a review. Plant Methods 11:29PubMedPubMedCentralCrossRefGoogle Scholar
  67. Imadi SR, Kazi AG, Ahanger MA, Gucel S, Ahmad P (2015) Plant transcriptomics and responses to environmental stress: an overview. J Genet 94:525–537PubMedCrossRefGoogle Scholar
  68. Jacoby RP, Millar AH, Taylor NL (2013) Investigating the role of respiration in plant salinity tolerance by analyzing mitochondrial proteomes from wheat and a salinity-tolerant amphiploid (wheat x Lophopyrum elongatum). J Proteome Res 12:4807–4829PubMedCrossRefGoogle Scholar
  69. Ji W, Cong R, Li S, Li R, Qin Z, Li Y, Zhou X, Chen S, Li J (2016) Comparative proteomic analysis of soybean leaves and roots by iTRAQ provides insights into response mechanisms to short-term salt stress. Front Plant Sci 7:573PubMedPubMedCentralGoogle Scholar
  70. Ji L, Zhou P, Zhu Y, Liu F, Li R, Qiu Y (2017) Proteomic analysis of rice seedlings under cold stress. Protein J 36:299–307PubMedCrossRefGoogle Scholar
  71. Jorrin-Novo (2016) Plant proteomics methods and protocols. Methods Mol Biol 1072:3–13CrossRefGoogle Scholar
  72. Kaler AS, Ray JD, Schapaugh WT, King CA, Purcell LC (2017) Genome-wide association mapping of canopy wilting in diverse soybean genotypes. Theor Appl Genet 130:2203–2217PubMedCrossRefGoogle Scholar
  73. Kang G, Li G, Xu W, Peng X, Han Q, Zhu Y, Guo T (2012) Proteomics reveals the effects of salicylic acid on growth and tolerance to subsequent drought stress in wheat. J Proteome Res 11:6066–6079PubMedCrossRefGoogle Scholar
  74. Kang YJ, Lee T, Lee J, Shim S, Jeong H, Satyawan D, Kim MY, Lee SH (2016) Translational genomics for plant breeding with the genome sequence explosion. Plant Biotechnol J 14:1057–1069PubMedCrossRefGoogle Scholar
  75. Kim ST, Kim SG, Agrawal GK, Kikuchi S, Rakwa R (2014) Rice proteomics: a model system for crop improvement and food security. Proteomics 14:593–610PubMedCrossRefGoogle Scholar
  76. Komatsu S, Wada T, Abalea Y, Nouri MZ, Nanjo Y, Nakayama N, Shimamura S, Yamamoto R, Nakamura T, Furukawa K (2009) Analysis of plasma membrane proteome in soybean and application to flooding stress response. J Proteome Res 8:4487–4499PubMedCrossRefGoogle Scholar
  77. Komatsu S, Kobayashi Y, Nishizawa K, Nanjo Y, Furukawa K (2010) Comparative proteomics analysis of differentially expressed proteins in soybean cell wall during flooding stress. Amino Acids 39:1435–1449PubMedCrossRefGoogle Scholar
  78. Komatsu S, Yamamoto A, Nakamura T, Nouri MZ, Nanjo Y, Nishizawa K, Furukawa K (2011) Comprehensive analysis of mitochondria in roots and hypocotyls of soybean under flooding stress using proteomics and metabolomics techniques. J Proteome Res 10:3993–4004PubMedCrossRefGoogle Scholar
  79. Komatsu S, Kamal AHM, Hossain Z (2014) Wheat proteomics: proteome modulation and abiotic stress acclimation. Front Plant Sci 5:684PubMedPubMedCentralCrossRefGoogle Scholar
  80. Kosova K, Vitamvas P, Planchon S, Renaut J, Vankova R, Prasil IT (2013) Proteome analysis of cold response in spring and winter wheat (Triticum aestivum) crowns reveals similarities in stress adaptation and differences in regulatory processes between the growth habits. J Proteome Res 12:4830–4845PubMedCrossRefGoogle Scholar
  81. Kumari A, Das P, Parida AK, Agarwa PK (2015) Proteomics, metabolomics, and ionomics perspectives of salinity tolerance in halophytes. Front Plant Sci 6:537PubMedPubMedCentralCrossRefGoogle Scholar
  82. Lee DG, Ahsan N, Lee SH, Lee JJ, Bahk JD, Kang KY, Lee BH (2009) Chilling stress-induced proteomic changes in rice roots. J Plant Physiol 166:1–11PubMedCrossRefGoogle Scholar
  83. Li L, Zhang Q, Huang D (2014) A review of imaging techniques for plant phenotyping. Sensors 14:20078–20111PubMedCrossRefGoogle Scholar
  84. Li W, Zhao F, Fang W, Xie D, Hou J, Yang X, Zhao Y, Tang Z, Nie L, Lv S (2015) Identification of early salt stress responsive proteins in seedling roots of upland cotton (Gossypium hirsutum L.) employing iTRAQ-based proteomic technique. Front Plant Sci 6:732PubMedPubMedCentralGoogle Scholar
  85. Li C, Sun B, Li Y, Liu C, Wu X, Zhang D, Shi Y, Song Y, Buckler ES, Zhang Z, Wang T, Li Y (2016) Numerous genetic loci identified for drought tolerance in the maize nested association mapping populations. BMC Genomics 17:894PubMedPubMedCentralCrossRefGoogle Scholar
  86. Li X, Guo Z, Lv Y, Cen X, Ding X, Wu H, Li X, Huang J, Xiong L (2017) Genetic control of the root system in rice under normal and drought stress conditions by genome-wide association study. PLoS Genet 13:e1006889PubMedPubMedCentralCrossRefGoogle Scholar
  87. Li D, Dossa K, Zhang Y, Wei X, Wang L, Zhang Y, Liu A, Zhou R, Zhang X (2018) GWAS uncovers differential genetic bases for drought and salt tolerances in sesame at the germination stage. Gene 9:87CrossRefGoogle Scholar
  88. Liu JX, Bennett J (2011) Reversible and irreversible drought-induced changes in the anther proteome of rice (Oryza sativa L.) genotypes IR64 and Moroberekan. Mol Plant 4:59–69PubMedCrossRefGoogle Scholar
  89. Liu XP, Yu LX (2017) Genome-wide association mapping of loci associated with plant growth and forage production under salt stress in alfalfa (Medicago sativa L.). Front Plant Sci 8:853PubMedPubMedCentralCrossRefGoogle Scholar
  90. Liu D, Ford KL, Roessner U, Natera S, Cassin AM, Patterson JH, Bacic A (2013) Rice suspension cultured cells are evaluated as a model system to study salt responsive networks in plants using a combined proteomic and metabolomic profiling approach. Proteomics 13:2046–2062PubMedCrossRefGoogle Scholar
  91. Longo V, Valizadeh KR, Michaletti A, Toorchi M, Zolla L, Rinalducci S (2017) Proteomic and physiological response of spring barley leaves to cold stress. Int J Plant Biol Res 5:1061Google Scholar
  92. Lu Y, Lam H, Pi E, Zhan Q, Tsai S, Wang C (2013) Comparative metabolomics in Glycine max and Glycine soja under salt stress to reveal the phenotypes of their offspring. J Agric Food Chem 61:8711–8721PubMedCrossRefGoogle Scholar
  93. Lu X, Chen X, Mu M, Wang J, Wang X, Wang D, Yin Z, Fan W, Wang S, Guo L, Ye W (2016) Genome-wide analysis of long noncoding RNAs and their responses to drought stress in cotton (Gossypium hirsutum L.). PLoS One 11:e0156723PubMedPubMedCentralCrossRefGoogle Scholar
  94. Ma H, Song L, Shu Y, Wang S, Niu J, Wang Z, Yu T, Gu W, Ma H (2012) Comparative proteomic analysis of seedling leaves of different salt tolerant soybean genotypes. J Proteome 75:1529–1546CrossRefGoogle Scholar
  95. Ma X, Feng F, Wei H, Mei H, Xu K, Chen S, Li T, Liang X, Liu H, Luo L (2016) Genome-wide association study for plant height and grain yield in rice under contrasting moisture regimes. Front Plant Sci 7:1801PubMedPubMedCentralGoogle Scholar
  96. Ma Q, Kang J, Long R, Zhang T, Xiong J, Zhang K, Wang T, Yang Q, Sun Y (2017) Comparative proteomic analysis of alfalfa revealed new salt and drought stress-related factors involved in seed germination. Mol Biol Rep 44:261–272PubMedCrossRefGoogle Scholar
  97. Manaa A, Ben Ahmed H, Valot B, Bouchet JP, Aschi-Smiti S, Causse M, Faurobert M (2011) Salt and genotype impact on plant physiology and root proteome variations in tomato. J Exp Bot 62:2797–2813PubMedCrossRefGoogle Scholar
  98. Mangin B, Casadebaig P, Cadic E, Blanchet N, Boniface MC, Carrère S, Gouzy J, Legrand L, Mayjonade B, Pouilly N, André T, Coque M, Piquemal J, Laporte M, Vincourt P, Munos S, Langlade NB (2017) Genetic control of plasticity of oil yield for combined abiotic stresses using a joint approach of crop modelling and genome-wide association. Plant Cell Environ 40:2276–2291PubMedCrossRefGoogle Scholar
  99. Maruyama K, Urano K, Yoshiwara K, Morishita Y, Sakurai N, Suzuki H (2014) Integrated analysis of the effects of cold and dehydration on rice metabolites, phytohormones, and gene transcripts. Plant Physiol 164:1759–1771PubMedPubMedCentralCrossRefGoogle Scholar
  100. Merchuk-Ovnat L, Silberman R, Laiba E, Maurer A, Pillen K, Faigenboim A, Fridman E (2018) Genome scan identifies flowering-independent effects of barley HsDry2.2 locus on yield traits under water deficit. J Exp Bot 69:1765–1779PubMedPubMedCentralCrossRefGoogle Scholar
  101. Michael TP, Jackson S (2013) The first 50 plant genomes. Plant Genome 6:1–7CrossRefGoogle Scholar
  102. Millet EJ, Welcker C, Kruijer W, Negro S, Coupel-Ledru A, Nicolas SD, Laborde J, Bauland C, Praud S, Ranc N, Presterl T, Tuberosa R, Bedo Z, Draye X, Usadel B, Charcosset A, Eeuwijk FV, Tardieu F (2016) Genome-wide analysis of yield in Europe: allelic effects vary with drought and heat scenarios. Plant Physiol 172:749–764PubMedPubMedCentralGoogle Scholar
  103. Mochida K, Shinozaki K (2011) Advances in omics and bioinformatics tools for system analyses of plant functions. Plant Cell Physiol 52:2017–2038PubMedPubMedCentralCrossRefGoogle Scholar
  104. Moreno-Risueno MA, Busch W, Benfey PN (2010) Omics meet networks-using systems approaches to infer regulatory networks in plants. Curr Opin Plant Biol 13:126–131PubMedCrossRefGoogle Scholar
  105. Muscolo A, Junker A, Klukas C, Weigelt-Fischer K, Riewe D, Altmann T (2015) Phenotypic and metabolic responses to drought and salinity of four contrasting lentil accessions. J Exp Bot 66:5467–5480PubMedPubMedCentralCrossRefGoogle Scholar
  106. Mwadzingeni L, Shimelis H, Rees DJG, Tsilo TJ (2017) Genome-wide association analysis of agronomic traits in wheat under droughtstressed and non-stressed conditions. PLoS One 12:e0171692PubMedPubMedCentralCrossRefGoogle Scholar
  107. Nakabayashi R, Saito K (2015) Integrated metabolomics for abiotic stress responses in plants. Curr Opin Plant Biol 24:10–16CrossRefGoogle Scholar
  108. Naveed SA, Zhang F, Zhang J, Zheng T-O, Meng L-J, Pang Y-L, Xu J-L, Li Z-K (2018) Identification of QTN and candidate genes for salinity tolerance at the germination and seedling stages in rice by genome-wide association analyses. Sci Rep 8:6505PubMedPubMedCentralCrossRefGoogle Scholar
  109. Ngara R, Ndimba R, Borch-Jensen J, Jensen ON, Ndimba B (2012) Identification and profiling of salinity stress – responsive proteins in Sorghum bicolor seedlings. J Proteome 75:4139–4150CrossRefGoogle Scholar
  110. Oliver SG, Winson MK, Kell DB, Baganz F (1998) Systemic functional analysis of the yeast genome. Trends Biotechnol 16:373–378PubMedCrossRefGoogle Scholar
  111. Oskuei BK, Yin X, Hashiguchi A, Bandehagh A, Komatsu S (2017) Proteomic analysis of soybean seedling leaf under waterlogging stress in a time-dependent manner. Biochim Biophys Acta, Proteins Proteomics 1865:1167–1177CrossRefGoogle Scholar
  112. Pan L, Meng C, Wang J, Ma X, Fan X, Yang Z, Zhou M, Zhang X (2018) Integrated omics data of two annual ryegrass (Lolium multiflorum L.) genotypes reveals core metabolic processes under drought stress. BMC Plant Biol 18:26PubMedPubMedCentralCrossRefGoogle Scholar
  113. Pandit E, Tasleem S, Barik SR, Mohanty DP, Nayak DK, Mohanty SP, Das S, Pradhan SK (2017) Genome-wide association mapping reveals multiple QTLs governing tolerance response for seedling stage chilling stress in indica rice. Front Plant Sci 8:552PubMedPubMedCentralCrossRefGoogle Scholar
  114. Pantaliao GF, Narciso M, Guimaraes C, Castro A, Colombari JM, Breseghello F, Rodrigues L, Vianello RP, Borba TO, Brondani C (2016) Genome wide association study (GWAS) for grain yield in rice cultivated under water deficit. Genetica 144:651–664PubMedCrossRefGoogle Scholar
  115. Patishtan J, Hartley TN, Fonseca de Carvalho R, Maathuis FJM (2018) Genome-wide association studies to identify rice salt-tolerance markers. Plant Cell Environ 41:970–982PubMedCrossRefGoogle Scholar
  116. Peng Z, Wang M, Li F, Lv H, Li C, Xia G (2009) A proteomic study of the response to salinity and drought stress in an introgression strain of bread wheat. Mol Cell Proteomics 8:2676–2268PubMedPubMedCentralCrossRefGoogle Scholar
  117. Peng Z, He S, Gong W, Xu F, Pan Z, Jia Y, Geng X, Du X (2018) Integration of proteomic and transcriptomic profiles reveals multiple levels of genetic regulation of salt tolerance in cotton. BMC Plant Biol 18:128PubMedPubMedCentralCrossRefGoogle Scholar
  118. Poland J (2015) Breeding-assisted genomics. Curr Opin Plant Biol 24:119–124PubMedCrossRefGoogle Scholar
  119. Qin P, Lin Y, Hu Y, Liu K, Mao S, Li Z, Wang J, Liu Y, Wei Y, Zheng Y (2016) Genome-wide association study of drought-related resistance traits in Aegilops tauschii. Genet Mol Biol 39:398–407PubMedPubMedCentralCrossRefGoogle Scholar
  120. Rhee SY, Mutwil M (2014) Towards revealing the functions of all genes in plants. Trends Plant Sci 19:213–221Google Scholar
  121. Samota MK, Bhatt L, Yadav DK, Garg N, Bajiya R (2017) Metabolomics for functional genomics. Int J Curr Microbiol App Sci 6:2531–2537CrossRefGoogle Scholar
  122. Sanchez DH, Schwabe F, Erban A, Udvardi MK, Kopka J (2012) Comparative metabolomics of drought acclimation in model and forage legumes. Plant Cell Environ 35:136–149PubMedCrossRefGoogle Scholar
  123. Sanchez-Bel P, Egea I, Sanchez-Ballesta MT, Sevillano L, Del Carmen Bolarin M, Flores FB (2012) Proteome changes in tomato fruits prior to visible symptoms of chilling injury are linked to defensive mechanisms, uncoupling of photosynthetic processes and protein degradation machinery. Plant Cell Physiol 53:470–484PubMedCrossRefGoogle Scholar
  124. Satismruti K, Senthil N, Vellaikumar S, Ranjani RV, Raveendran M (2013) Plant ionomics: a platform for identifying novel gene regulating plant mineral nutrition. Am J Plant Sci 4:309–1315CrossRefGoogle Scholar
  125. Savvides A, Ali S, Tester M, Fotopoulos V (2016) Chemical priming of plants against multiple abiotic stresses: Mission possible? Cell 21:329–340Google Scholar
  126. Schläppi MR, Jackson AK, Eizenga GC, Wang A, Chu C, Shi Y, Shimoyama N, Boykin DL (2017) Assessment of five chilling tolerance traits and GWAS mapping in rice using the USDA mini-core collection. Front Plant Sci 8:957PubMedPubMedCentralCrossRefGoogle Scholar
  127. Shen Q, Yu J, Fu L, Wu L, Dai F, Jiang L, Wu D (2018) Zhang G (2018) Ionomic, metabolomic and proteomic analyses reveal molecular mechanisms of root adaption to salt stress in Tibetan wild barley. Plant Physiol Biochem 123:319–330PubMedCrossRefGoogle Scholar
  128. Shi Y, Gao L, Wu Z, Zhang X, Wang M, Zhang C, Zhang F, Zhou Y, Li Z (2017) Genome-wide association study of salt tolerance at the seed germination stage in rice. BMC Plant Biol 17:92PubMedPubMedCentralCrossRefGoogle Scholar
  129. Shikha M, Kanika A, Rao AR, Mallikarjuna MG, Gupta HS, Nepolean T (2017) Genomic selection for drought tolerance using genome-wide SNPs in maize. Front Plant Sci 8:550PubMedPubMedCentralCrossRefGoogle Scholar
  130. Silvente S, Sobolev AP, Lara M (2012) Metabolite adjustments in drought tolerant and sensitive soybean genotypes in response to water stress. PLoS One 7:e38554PubMedPubMedCentralCrossRefGoogle Scholar
  131. Singh UM, Sareen P, Sngar RS, Kumar A (2013) Plant ionomics: a newer approach to study mineral transport and its regulation. Acta Physiol Plant 35:2641–2653CrossRefGoogle Scholar
  132. Skliros D, Kalloniati C, Karalias G, Skaracis GN, Rennenberg H, Flemetakis E (2018) Global metabolomics analysis reveals distinctive tolerance mechanisms in different plant organs of lentil (Lens culinaris) upon salinity stress. Plant Soil 429:451–468CrossRefGoogle Scholar
  133. Song Y, Zhang C, Ge W, Zhang Y, Burlingame AL, Guo Y (2011) Identification of NaCl stress-responsive apoplastic proteins in rice shoot stems by 2D-DIGE. J Proteome 74:1045–1067CrossRefGoogle Scholar
  134. Sukumaran S, Reynolds MP, Sansaloni C (2018) Genome-wide association analyses identify QTL hotspots for yield and component traits in durum wheat grown under yield potential, drought, and heat stress environments. Front Plant Sci 9:81PubMedPubMedCentralCrossRefGoogle Scholar
  135. Sun C, Gao X, Chen X, Fu J, Zhang Y (2016) Metabolic and growth responses of maize to successive drought and re-watering cycles. Agric Water Manag 172:62–73CrossRefGoogle Scholar
  136. Tan M, Liao F, Hou L, Wang J, Wei L, Jian H, Xu X, Li J, Liu L (2017) Genome-wide association analysis of seed germination percentage and germination index in Brassica napus L. under salt and drought stresses. Euphytica 213:40CrossRefGoogle Scholar
  137. Tavakol E, Elbadry N, Tondelli A, Cattivelli L, Rossini L (2016) Genetic dissection of heading date and yield under Mediterranean dry climate in barley (Hordeum vulgare L.). Euphytica 212:343–353CrossRefGoogle Scholar
  138. Tenenboim H, Burgos A, Willmitzer L, Brotman Y (2016) Using lipidomics for expanding the knowledge on lipid metabolism in plants. Biochimie 130:91e96CrossRefGoogle Scholar
  139. Thimm O, Blaesing O, Gibon Y, Nagel A, Meyer S, Kruger P, Selbig J, Muller LA, Rhee SY, Stitt M (2004) MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J 37:914–939PubMedPubMedCentralCrossRefGoogle Scholar
  140. Tian H, Lam SM, Shui G (2017) Metabolomics, a powerful tool for agricultural research. Int J Mol Sci 17:1871CrossRefGoogle Scholar
  141. Ubbens JR, Stavness I (2017) Deep plant phenomics: a deep learning platform for complex plant phenotyping tasks. Front Plant Sci 8:1190PubMedPubMedCentralCrossRefGoogle Scholar
  142. Uhrig RG, Moorhead GB (2013) Plant proteomics: current status and future prospects. J Proteome 88:34–36CrossRefGoogle Scholar
  143. Ullah N, Yüce M, Neslihan Öztürk Gökçe Z, Budak H (2017) Comparative metabolite profiling of drought stress in roots and leaves of seven Triticeae species. BMC Genomics 18:969PubMedPubMedCentralCrossRefGoogle Scholar
  144. Unamba CIN, Nag A, Sharma RK (2015) Next generation sequencing technologies: the doorway to the unexplored genomics of non-model plants. Front Plant Sci 6:1074PubMedPubMedCentralCrossRefGoogle Scholar
  145. Van Emon JM (2016) The omics revolution in agricultural research. J Agric Food Chem 64:36–44PubMedCrossRefGoogle Scholar
  146. Vanderschuren H, Lentz E, Zainuddin I, Gruissem W (2013) Proteomics of model and crop plant species: status, current limitations and strategic advances for crop improvement. J Proteome 93:5–19CrossRefGoogle Scholar
  147. Vitamvas P, Prasil IT, Kosova K, Planchon S, Renaut J (2012) Analysis of proteome and frost tolerance in chromosome 5A and 5B reciprocal substitution lines between two winter wheats during long-term cold acclimation. Proteomics 12:68–85PubMedCrossRefGoogle Scholar
  148. Wade LJ, Salekdeh GH, Siopongco J, Ghareyazie B, Bennett J (2002) Proteomic analysis of rice leaves during drought stress and recovery. Proteomics 2:1131–1145PubMedCrossRefGoogle Scholar
  149. Wallace JG, Buckler ES, Zhang X, Beyene Y, Olsen M, Semagn K, Prasanna BM (2016) Genome-wide association for plant height and flowering time across 15 tropical maize populations under managed drought stress and well-watered conditions in sub-Saharan Africa. Crop Sci 56:2365–2378CrossRefGoogle Scholar
  150. Wang WQ, Moller IM, Song SQ (2012) Proteomic analysis of embryonic axis of Pisum sativum seeds during germination and identification of proteins associated with loss of desiccation tolerance. J Proteome 77:68–86CrossRefGoogle Scholar
  151. Wang X, Dinler BS, Vignjevic M, Jacobsen S, Wollenweber B (2015) Physiological and proteome studies of responses to heat stress during grain filling in contrasting wheat cultivars. Plant Sci 230:33–50PubMedCrossRefGoogle Scholar
  152. Wang N, Wang ZP, Liang XL, Weng JF, Lv XL, Zhang DG, Yang J, Yong HJ, Li MS, Li FH, Jiang LY, Zhang SH, Hao ZF, Li XH (2016) Identification of loci contributing to maize drought tolerance in a genome-wide association study. Euphytica 210:165–179CrossRefGoogle Scholar
  153. Wang Y, Xu C, Zhang B, Wu M, Chen G (2017) Physiological and proteomic analysis of rice (Oryza sativa L.) in flag leaf during flowering stage and milk stage under drought stress. Plant Growth Regul 82:201–218CrossRefGoogle Scholar
  154. Watanabe T, Maejima E, Ypshimura T, Urayama M, Yamauchi A, Owadano M, Okada R, Osaki M, Kanayama Y, Shinano T (2016) The ionomic study of vegetable crops. PLoS One 11:e0160273PubMedPubMedCentralCrossRefGoogle Scholar
  155. Watson SJ, Sowden RG, Jarvis P (2018) Abiotic stress-induced chloroplast proteome remodelling: a mechanistic overview. J Exp Bot 69:2773–2781PubMedCrossRefGoogle Scholar
  156. Welti R, Shah J, Li W, Li M, Chen J, Burke JJ, Fauconnier ML, Chapman K, Chye ML, Wang X (2007) Plant lipidomics: discerning biological function by profiling plant complex lipids using mass spectrometry. Front Biosci 12:2494–2506PubMedCrossRefGoogle Scholar
  157. White JW, Andrade-Sanchez P, Gore MA, Bronson KF, Coffelt TA, Conley TA, Conley MM, Feldman KA, French AN, Heun JT, Hunsaker DJ, Jenks MA, Kimball B, Roth RL, Strand RJ, Thorp KR, Wall GW, Wang G (2012) Field-based phenomics for plant genetics research. Field Crop Res 133:101–112CrossRefGoogle Scholar
  158. Widodo PJH, Newbigin E, Tester M, Bacic A, Roessner U (2009) Metabolic responses to salt stress of barley (Hordeum vulgare L.) cultivars, Sahara and Clipper, which differ in salinity tolerance. J Exp Bot 60:4089–4103PubMedPubMedCentralCrossRefGoogle Scholar
  159. Winkler H (1920) Verbreitung und ursache der parthenogenesis im pflanzen und tierreiche. Fischer, JenaCrossRefGoogle Scholar
  160. Witzel K, Weidner A, Surabhi GK, Börner A, Mock HP (2009) Salt stress-induced alterations in the root proteome of barley genotypes with contrasting response towards salinity. J Exp Bot 60:3545–3557PubMedPubMedCentralCrossRefGoogle Scholar
  161. Woldesemayat AA, Modise DM, Gemeildien J, Ndimba BK, Christoffels A (2018) Cross-species multiple environmental stress responses: an integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and related model species. PLoS One 13:e0192678PubMedPubMedCentralCrossRefGoogle Scholar
  162. Wu D, Shen Q, Qiu L, Han Y, Ye L, Jabeen Z, Shu Q, Zhang G (2014) Identification of proteins associated with ion homeostasis and salt tolerance in barley. Proteomics 14:1381–1392PubMedCrossRefGoogle Scholar
  163. Yaish MW, Al-Lawati A, Al-Harrasi I, Patankar HV (2018) Genome-wide DNA methylation analysis in response to salinity in the model plant caliph medic (Medicago truncatula). BMC Genomics 19:78PubMedPubMedCentralCrossRefGoogle Scholar
  164. Yin X, Sakata K, Nanjo Y, Komatsu S (2014) Analysis of initial changes in the proteins of soybean root tip under flooding stress using gel-free and gel-based proteomic techniques. J Proteome 106:1–16CrossRefGoogle Scholar
  165. Yin Y, Qi F, Gao L, Rao S, Yang Z, Fang W (2018) iTRAQ-based quantitative proteomic analysis of dark-germinated soybeans in response to salt stress. RSC Adv 8:17905CrossRefGoogle Scholar
  166. Yousuf PY, Ahmad A, Ganie AH, Sareer O, Krishnapriya V, Aref IM, Iqbal M (2017) Antioxidant response and proteomic modulations in Indian mustard grown under salt stress. Plant Growth Regul 81:31–50CrossRefGoogle Scholar
  167. Yu L-X (2017) Identification of single-nucleotide polymorphic loci associated with biomass yield under water deficit in alfalfa (Medicago sativa L.) using genome-wide sequencing and association mapping. Front Plant Sci 8:1152PubMedPubMedCentralCrossRefGoogle Scholar
  168. Yu L-X, Liu X, Boge W, Liu X-P (2016) Genome-wide association study identifies loci for salt tolerance during germination in autotetraploid alfalfa (Medicago sativa L.) using genotyping-by-sequencing. Front Plant Sci 7:956PubMedPubMedCentralGoogle Scholar
  169. Yu J, Zao W, He Q, Kim TS, Park YJ (2017) Genome-wide association study and gene set analysis for understanding candidate genes involved in salt tolerance at the rice seedling stage. Mol Gen Genomics 292:1391–1403CrossRefGoogle Scholar
  170. Yugi K, Kubota H, Hatano A, Kuroda S (2016) Trans-omics: how to reconstruct biochemical networks across multiple ‘omics’ layers. Trends Biotechnol 34:276–290PubMedCrossRefGoogle Scholar
  171. Zadraznik T, Hollung K, Egge-Jacobsen W, Meglic V, Sustar-Vozlic J (2013) Differential proteomic analysis of drought stress response in leaves of common bean (Phaseolus vulgaris L.). J Proteome 78:254–272CrossRefGoogle Scholar
  172. Zeng A, Chen P, Korth K, Hancock F, Pereira A, Brye K, Wu C, Shi A (2017) Genome-wide association study (GWAS) of salt tolerance in worldwide soybean germplasm lines. Mol Breed 37:30CrossRefGoogle Scholar
  173. Zhang C, Shi S (2018) Physiological and proteomic responses of contrasting alfalfa (Medicago sativa L.) varieties to PEG-induced osmotic stress. Front Plant Sci 9:242PubMedPubMedCentralCrossRefGoogle Scholar
  174. Zhang M, Lv D, Ge P, Bian Y, Chen G, Zhu G, Li X, Yan Y (2014) Phosphoproteome analysis reveals new drought response and defense mechanisms of seedling leaves in bread wheat (Triticum aestivum L.). J Proteome 109:290–308CrossRefGoogle Scholar
  175. Zhang X, Warburton ML, Setter T, Liu H, Xue H, Yang N, Yan J, Xiao Y (2016) Genome wide association studies of drought related metabolic changes in maize using an enlarged SNP panel. Theor Appl Genet 129:1449–1463PubMedCrossRefGoogle Scholar
  176. Zhao Q, Chen SX, Dai SJ (2013) C4 photosynthetic machinery: insights from maize chloroplast proteomics. Front Plant Sci 4:1–5Google Scholar
  177. Zhuang J, Zhang J, Hou XL, Wang F, Xiong AS (2014) Transcriptomic, proteomic, metabolomics and functional genomic approaches for the study of abiotic stress in vegetable crops. Crit Rev Plant Sci 33:225–237CrossRefGoogle Scholar
  178. Zorb C, Schmitt S, Muhling KH (2010) Proteomic changes in maize roots after short-term adjustment to saline growth conditions. Proteomics 10:4441–4449PubMedCrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Zahide Neslihan Ozturk Gokce
    • 1
    Email author
  • Seyda Akbas
    • 1
  • Sefa Ayten
    • 1
  • M. Hussain Azimi
    • 1
  • Reyhan Das
    • 1
  • Saime Buse Guven
    • 1
  • Ebrar Karabulut
    • 1
  • Seher Omezli
    • 1
  • Zehra Uzer
    • 1
  • Bayram Ali Yerlikaya
    • 1
  • Allah Bakhsh
    • 1
  1. 1.Department of Agricultural Genetic Engineering, Ayhan Sahenk Faculty of Agricultural Sciences and TechnologiesNigde Omer Halisdemir UniversityNigdeTurkey

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